• Communications for Statistical Applications and Methods
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• v.17 no.6
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• pp.791-801
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• 2010

This study reviews the concept of disclosure, disclosure risks, and uniqueness. The number of uniqueness in the population is of great importance in evaluating the disclosure risk of micro data files. We approach this problem by considering some basic superpopulation models including the Multinomial-Dirichlet model, the Poisson- Gamma model of Bethlehem et al. (1990) and Takemura (1997), and the Modified Multinomial-Dirichlet model. We decided the critical population size of each superpopulation model for four different superpopulation models.

• Communications for Statistical Applications and Methods
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• v.10 no.1
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• pp.79-88
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• 2003

In this paper, we study the efficiency of the stratified estimator in related with the variance lower bound of Horvitz-Thompson estimator subject to the superpopulation model. Especially, we compare the variance lower bound of optimum allocation with that of power allocation subject to Dalenius-Hedges stratification.

• The Korean Journal of Applied Statistics
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• v.5 no.1
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• pp.9-17
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• 1992

In this paper we give a Bayesian approach to problems of estimation for the ratio in finite populations. Adopting the Ericson's superpopulatin approach in which the finite population of size N is viewed as arising form a random sample of N units from some superpopulation. We derive the exact posterior of the ratio under the noninformative prior on superpopulation parameters. Based on our results we compute an exact Bayesian confidence interval and compare this with the existing methods.

• Communications for Statistical Applications and Methods
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• v.14 no.3
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• pp.667-677
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• 2007

In this paper, we propose a method for estimating the mean of a population which has a linear trend, when both n, the sample size, and k, the reciprocal of the sampling fraction, are odd numbers. The proposed method, not having the drawbacks of centered systematic sampling, centered modified sampling and centered balanced sampling, consists of selecting a sample by balanced systematic sampling and estimating the population mean by using interpolation. We compare the efficiency of the proposed method and existing methods under the criterion of the expected mean square error based on the infinite superpopulation model.

• Journal of the Korean Data and Information Science Society
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• v.25 no.3
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• pp.685-696
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• 2014

In this paper, we develop Bayesian inference of the finite population mean with the assumption of posterior linearity rather than normality of the superpopulation in the presence of auxiliary information under the balanced loss function. We compare the performance of the optimal Bayes estimator under the balanced loss function with ones of the classical ratio estimator and the usual Bayes estimator in terms of the posterior expected losses, risks and Bayes risks.

• Journal of the Korean Statistical Society
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• v.29 no.4
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• pp.455-471
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• 2000

A new method is developed for estimating the mean of a population which has a linear trend. The proposed estimator is based on the balanced systematic sampling method and the concept of interpolation. The efficiency of the proposed method is compared with that of existing methods.

• Communications for Statistical Applications and Methods
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• v.11 no.1
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• pp.1-12
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• 2004

In this paper, Yates' end corrections method is centralized to estimate the mean of a population which has a linear trend in the case of k (the reciprocal of the sampling fraction) even. The efficiency of the resultant method is compared with that of existing methods.

• Journal of the Korean Data and Information Science Society
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• v.13 no.2
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• pp.365-379
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• 2002

We apply the techniques of interpolation and extrapolation to derive a new estimator based on centered modified systematic sampling for the mean of a population which has a linear trend. The efficiency of the proposed estimation method is compared with that of various existing methods. An illustrative numerical example is given.

• Communications for Statistical Applications and Methods
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• v.9 no.1
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• pp.175-185
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• 2002

A method is proposed for efficiently estimating the mean of a population which has a linear trend. The proposed estimator is based on the centered modified systematic sampling method and the concept of interpolation. Using the expected mean square error criterion, it is shown that the proposed method is more efficient than conventional methods in most real cases.

• Communications for Statistical Applications and Methods
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• v.2 no.1
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• pp.155-165
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• 1995

초모집단(superpopulation)으로 부터 반복적으로 유한모집단을 추출할 때, 이미 조사된 자료들을 이용하면 현재의 유한모집단 모수들을 ㄷ더 효율적으로 추정할 수 있다. 이러한 문제에 대하여 Ericson(1969)이 유한모집단 표본추출에서 베이지안 분석을 하였고, Ghosh와 Meeden(1986)은 정규 초모집단을 가정하여 유한모집단 평균의 경험적 베이즈 추정을 하였다. Nandram과 Sedransk (1993)는 Ghosh와 Meeden(1986)의 유한모집단들의 분산이 모두 같다는 가정들을 완화하여 유한집단 평균의 경험적 베이즈 추정을 하였다. 본 연구는 Nandram과 Sedransk의 결과를 층과표본추출의 경우로 일반화 하였다.